Jingrui Zhang, Jian Wang, Chaoyuan Yue, and Lingling Zhuang
Hydrothermal scheduling, valve point effect, acceleration, PSO
Short-term hydrothermal scheduling (STHS) is one of the important optimization problems in power systems. A mathematical model considering various constraints is established to minimize the total thermal fuel cost in the STHS problem. To solve this problem, an acceleration-based particle swarm optimization (APSO) approach is proposed. In the proposed approach, an adaptive mutation operation is introduced to enhance the swarm diversity; a differential evolutionary (DE) algorithm is employed as an acceleration operation to speed the convergence rate; a novel inertia weight design mechanism is developed to balance global exploration and local search of the APSO algorithm; a repair strategy on equality constraints of the problem is proposed to avoid penalty function approach as much as possible. Three hydrothermal test cases in literature are considered to compare the results obtained by the proposed approach with other population-based algorithms. Two other particle swarm optimization (PSO) versions are also implemented on the same cases to compare the detailed statistic properties of them with the proposed one.
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